A loading and unloading worker multi-source information fusion loading and unloading behavior monitoring and analysis system
By integrating multi-source information into a loading and unloading behavior monitoring system, combined with visual and force measurement monitoring, the problems of low accuracy and difficulty in accountability during the loading and unloading process have been solved. This has enabled high-precision loading and unloading behavior analysis and data traceability, thereby reducing the cargo damage rate.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- HARBIN INST OF TECH
- Filing Date
- 2023-05-16
- Publication Date
- 2026-05-19
AI Technical Summary
In existing technologies, the accuracy of machine vision analysis of loading and unloading behavior is low, making it impossible to accurately determine whether there is violent handling during the loading and unloading process, resulting in a high rate of cargo damage and difficulty in assigning responsibility.
A multi-source information fusion monitoring system is adopted, which combines visual monitoring and force measurement monitoring. Various information during the loading and unloading process is collected through sensors and image acquisition devices, and the loading and unloading behavior is judged by deep learning algorithms and weighted scoring mechanisms.
It enables high-precision monitoring and data traceability of loading and unloading activities, reduces cargo damage rate, and improves the reliability and accountability of the loading and unloading process.
Smart Images
Figure CN116682055B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of logistics management equipment technology, and in particular to a multi-source information fusion system for monitoring and analyzing loading and unloading behavior of loading and unloading workers. Background Technology
[0002] With the development of express delivery and civil aviation passenger transport, a large number of parcels and passenger baggage are handled. Improper handling can easily lead to damage or even scrapping of these items. The lack of reliable, traceable data also increases the difficulty of assigning responsibility among senders, recipients, and carriers. Therefore, standardized and reasonable loading and unloading, along with data collection during the process, can effectively reduce damage rates and facilitate accountability in the event of future damage. However, most express delivery companies in my country have low levels of automation and mechanization, with a significant amount of manual loading and unloading. Their technological equipment and facilities are outdated, resulting in low sorting and transshipment rates for transport vehicles and inefficient warehouse layout. Therefore, a highly intelligent and traceable system is urgently needed to monitor the loading and unloading activities of cargo handlers.
[0003] Currently, the main method for analyzing loading and unloading behavior in existing technologies is through machine vision. This involves setting up cameras to collect video information of loading and unloading workers during the handling of goods, analyzing the positional relationships of the workers' joints, and determining the handling speed and release angle of the goods based on their position in the video frames. However, this method has low accuracy; the judgment of the goods' position and speed from each frame of the video has a large error, and it cannot determine whether the damage was caused by the goods being released and falling onto the conveyor belt at excessive speed. Summary of the Invention
[0004] The purpose of this invention is to provide a multi-source information fusion system for monitoring and analyzing loading and unloading behavior of loading and unloading workers. This system is used to monitor and analyze the loading and unloading behavior of loading and unloading workers by using multiple sensor information for analysis. It has the characteristics of accuracy, reliability, multi-source information fusion, and data traceability.
[0005] To achieve the above objectives, the present invention provides a multi-source information fusion system for monitoring and analyzing loading and unloading behavior of loading and unloading workers, including a transmission mechanism, a force measurement and monitoring mechanism, and a visual monitoring mechanism;
[0006] The transmission mechanism includes a conveyor support and a conveyor belt, the conveyor belt being wound around the conveyor support;
[0007] The force monitoring mechanism includes an auxiliary conveying platform, a load-bearing plate, and a weighing sensor. The auxiliary conveying platform is located in the middle of the conveying mechanism. The conveyor belt is connected to the auxiliary conveying platform. The auxiliary conveying platform is provided with a weighing chamber. The weighing sensor is located in the weighing chamber. The load-bearing plate is installed on the weighing sensor.
[0008] The visual monitoring mechanism includes a support frame and an image acquisition device. The image acquisition device is mounted on the support frame and is used to acquire video information during the loading and unloading process.
[0009] Preferably, the auxiliary conveying platform is further provided with a spring damper, the spring damper is fixedly connected to the upper end of the weighing sensor, and the load-bearing plate is fixedly connected to the upper end of the spring damper.
[0010] Preferably, the conveyor belt is a flexible conveyor belt.
[0011] Preferably, the support frame is arranged around the conveying mechanism, and multiple image acquisition devices are provided, which are evenly distributed on the support frame. The image acquisition devices are used to collect information on the body joint positions of loading and unloading workers and the position, posture, and speed of the goods when they are released from their hands.
[0012] A monitoring and analysis method for a multi-source information fusion system for monitoring and analyzing loading and unloading behavior of loading and unloading workers includes the following steps:
[0013] (1) Visual monitoring agencies collect behavioral information
[0014] When personnel handle goods, the image acquisition device captures the body position of the loading and unloading workers and the position, posture and speed of the goods when they are released from their hands. The pre-trained deep learning algorithm is used to determine whether there is any violent loading and unloading behavior.
[0015] (2) Force monitoring agencies collect force source information
[0016] Personnel place goods on the conveyor belt, which drives the load-bearing plate to press down on the weighing sensor. The weighing sensor measures the impact load of the goods being placed. After the goods are placed, the conveyor belt returns to a stable state, and the weighing sensor measures the static load of the goods. The impact load and static load are evaluated together to analyze whether the goods have been violently loaded or unloaded from the perspective of force source information.
[0017] (3) Weighted analysis to determine if violent loading and unloading occurs
[0018] Both the visual monitoring agency and the force monitoring agency are connected to the monitoring center via signals. The visual monitoring agency and the force monitoring agency transmit their judgment results to the monitoring center. The monitoring center uses a weighted scoring mechanism to arrive at the final judgment on whether the loading and unloading workers have engaged in violent dismantling behavior.
[0019] The beneficial effects of this invention are:
[0020] This invention designs an auxiliary conveyor platform to measure the impact load and static load of goods placed on the conveyor belt, thereby achieving high-precision monitoring of the loading and unloading process and providing traceable data. Combined with camera vision analysis of workers' loading and unloading behavior, it meets the requirements of both analyzing the actions of loading and unloading workers and analyzing the loading and unloading forces of goods with high precision.
[0021] This multi-source information fusion-based loading and unloading behavior monitoring and analysis system is characterized by accuracy, reliability, multi-source information integration, and data traceability. It is suitable for analyzing the loading and unloading behavior of workers in express logistics and airport baggage handling, and meets the requirements for both worker motion analysis and high-precision analysis of cargo loading and unloading forces.
[0022] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description
[0023] Figure 1 This is a schematic diagram of an embodiment of a loading and unloading behavior monitoring and analysis system based on multi-source information fusion of loading and unloading workers according to the present invention;
[0024] Figure 2 This is a schematic diagram of a conveyor support for a multi-source information fusion-based loading and unloading behavior monitoring and analysis system for loading and unloading workers, according to the present invention.
[0025] Figure 3 This is a schematic diagram of the force monitoring mechanism of a loading and unloading behavior monitoring and analysis system based on multi-source information fusion of loading and unloading workers, according to the present invention.
[0026] Figure 4 This is a schematic diagram of an auxiliary conveying platform for a multi-source information fusion-based loading and unloading behavior monitoring and analysis system for loading and unloading workers, based on the present invention.
[0027] Figure 5 This is a schematic diagram of the connection between the load-bearing plate and the weighing sensor in a multi-source information fusion monitoring and analysis system for loading and unloading workers according to the present invention.
[0028] Figure 6 This is a schematic diagram of the analysis method for loading and unloading behavior according to the present invention.
[0029] Figure label:
[0030] 1. Transmission mechanism; 101. Conveying support; 102. Conveying belt; 103. Conveying platform; 2. Force monitoring mechanism; 201. Auxiliary conveying platform; 202. Load-bearing plate; 203. Weighing sensor; 204. Weighing chamber; 205. Spring damper; 3. Visual monitoring mechanism; 301. Support frame; 302. Image acquisition device. Detailed Implementation
[0031] The present invention will be further described below with reference to embodiments.
[0032] Example
[0033] Please see Figures 1 to 6 As shown in the figure, the present invention provides a multi-source information fusion system for monitoring and analyzing loading and unloading behavior of loading and unloading workers, including a transmission mechanism 1, a force monitoring mechanism 2 and a visual monitoring mechanism 3; the transmission mechanism 1 includes a conveying support 101 and a conveyor belt 102, two symmetrically arranged conveying platforms 103 are provided on both sides of the conveying support, and the conveyor belt 102 is wound around the conveying support 101; the conveyor belt 102 is used to transport goods, and the goods are transferred to the main conveyor belt 102 through the conveyor belt 102.
[0034] The force monitoring mechanism 2 includes an auxiliary conveying platform 201, a load-bearing plate 202, and load cells 203. The auxiliary conveying platform 201 is located in the middle of the conveying mechanism, between two conveying platforms 103, and the conveyor belt 102 overlaps with the auxiliary conveying platform 201. A weighing chamber 204 is provided on the auxiliary conveying platform 201, and the load cells 203 are installed inside the weighing chamber 204. The load-bearing plate 202 is mounted on the load cells 203. Four load cells 203 are provided, located at the four corners of the weighing chamber 204 to ensure even force distribution. Simultaneous weighing and monitoring by the four load cells improves the accuracy of force source data acquisition.
[0035] The auxiliary conveying platform 201 is also equipped with a spring damper 205, which is fixedly connected to the upper end of the load cell 203. The load-bearing plate 202 is fixedly connected to the upper end of the spring damper 205. The spring damper 205 acts as a buffer to prevent excessive impact force from damaging the load cell 203 when placing goods. The conveyor belt 102 is a flexible conveyor belt 102. When goods are placed on the conveyor belt 102, they are subjected to the force of their own weight, causing the goods to press down and contact the conveyor belt 102 with the load-bearing plate 202, allowing the load cell 203 to measure the impact force. After the goods are placed stably, the load cell 203 can monitor the static force of the goods after they have stabilized.
[0036] The visual monitoring mechanism 3 includes a support frame 301 and image acquisition devices 302. The image acquisition devices 302 are mounted on the support frame 301 and are used to collect video information during the loading and unloading process. The support frame 301 is positioned around the conveyor mechanism. Multiple image acquisition devices 302 are evenly distributed on the support frame 301. These devices collect information on the body joint positions of the loading and unloading workers and the position, posture, and speed of the goods when they are released. Specifically, the image acquisition devices 302 are positioned on the support frame 301 in front of, above, to the left and right of the workers' standing positions, observing the workers and goods from multiple angles. The collected image information is input into a deep neural network to identify the workers' body joint positions and the position, posture, and speed of the goods when they are released.
[0037] The monitoring and analysis methods include the following steps:
[0038] (1) Visual monitoring agencies collect behavioral information
[0039] When personnel handle goods, the image acquisition device captures the body position of the loading and unloading workers and the position, posture and speed of the goods when they are released from their hands. The pre-trained deep learning algorithm is used to determine whether there is any violent loading and unloading behavior.
[0040] (2) Force monitoring agencies collect force source information
[0041] Personnel place goods on the conveyor belt, which drives the load-bearing plate to press down on the weighing sensor. The weighing sensor measures the impact load of the goods being placed. After the goods are placed, the conveyor belt returns to a stable state, and the weighing sensor measures the static load of the goods. The impact load and static load are evaluated together to analyze whether the goods have been violently loaded or unloaded from the perspective of force source information.
[0042] (3) Weighted analysis to determine if violent loading and unloading occurs
[0043] Both the visual monitoring agency and the force monitoring agency are connected to the monitoring center via signals. The visual monitoring agency and the force monitoring agency transmit their judgment results to the monitoring center. The monitoring center uses a weighted scoring mechanism to finally obtain the loading and unloading behavior analysis results under the multi-source information fusion mechanism. This not only improves the accuracy of the single analysis mechanism, but also records a large amount of data on the loading and unloading process from the perspective of multi-source information, providing a means for future accountability and tracing.
[0044] Therefore, the present invention adopts the above-mentioned multi-source information fusion loading and unloading behavior monitoring and analysis system for loading and unloading workers. Through the information fusion of multi-source sensor signals, it can realize the monitoring and analysis of loading and unloading behavior of loading and unloading workers, and provide handling data support for passengers, cargo senders, recipients and logistics parties, thereby reducing disputes over cargo damage.
[0045] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.
Claims
1. A multi-source information fusion system for monitoring and analyzing loading and unloading behavior of loading and unloading workers, characterized in that: This includes transmission mechanisms, force measurement and monitoring mechanisms, and visual monitoring mechanisms; The transmission mechanism includes a conveyor support and a conveyor belt, the conveyor belt being wound around the conveyor support; The force monitoring mechanism includes an auxiliary conveying platform, a load-bearing plate, and a weighing sensor. The auxiliary conveying platform is located in the middle of the transmission mechanism. The conveyor belt is connected to the auxiliary conveying platform. The auxiliary conveying platform is provided with a weighing chamber. The weighing sensor is located in the weighing chamber. The load-bearing plate is installed on the weighing sensor. The visual monitoring mechanism includes a support frame and an image acquisition device. The image acquisition device is mounted on the support frame and is used to acquire video information during the loading and unloading process. The monitoring and analysis method of the above-mentioned multi-source information fusion monitoring and analysis system for loading and unloading workers includes the following steps: (1) Visual monitoring agencies collect behavioral information When personnel handle goods, the image acquisition device captures the position of the loading and unloading workers' body joints and the position, posture and speed of the goods when they are released from their hands. The pre-trained deep learning algorithm is used to determine whether there is any violent loading and unloading behavior. (2) Force monitoring agencies collect force source information Personnel place goods on the conveyor belt, which drives the load-bearing plate to press down on the weighing sensor. The weighing sensor measures the impact load of the goods being placed. After the goods are placed, the conveyor belt returns to a stable state, and the weighing sensor measures the static load of the goods. The impact load and static load are evaluated together to analyze whether the goods have been violently loaded or unloaded from the perspective of force source information. (3) Weighted analysis to determine if violent loading and unloading exists. Both the visual monitoring agency and the force monitoring agency are connected to the monitoring center via signals. The visual monitoring agency and the force monitoring agency transmit their judgment results to the monitoring center. The monitoring center uses a weighted scoring mechanism to arrive at the final judgment on whether the loading and unloading workers have engaged in violent dismantling behavior.
2. The loading and unloading behavior monitoring and analysis system based on multi-source information fusion of loading and unloading workers according to claim 1, characterized in that: The auxiliary conveying platform is also equipped with a spring damper, which is fixedly connected to the upper end of the weighing sensor, and the load-bearing plate is fixedly connected to the upper end of the spring damper.
3. The loading and unloading behavior monitoring and analysis system based on multi-source information fusion of loading and unloading workers according to claim 1, characterized in that: The conveyor belt is a flexible conveyor belt.
4. The loading and unloading behavior monitoring and analysis system based on multi-source information fusion of loading and unloading workers according to claim 1, characterized in that: The support frame is arranged around the transmission mechanism, and multiple image acquisition devices are evenly distributed on the support frame. The image acquisition devices are used to collect information on the position of the loading and unloading workers' body joints and the position, posture and speed of the goods when they are released from their hands.